30 citations · 33 across the 4 of their papers we have counts for
4 papers
Adaptive Reward Design for Reinforcement Learning
Minjae Kwon, Ingy ElSayed-Aly, Lu Feng
There is a surge of interest in using formal languages such as Linear Temporal Logic (LTL) to precisely and succinctly specify complex tasks and derive reward functions for Reinfor…
Distributional Probabilistic Model Checking
Ingy Elsayed-Aly, David Parker, Lu Feng
Probabilistic model checking can provide formal guarantees on the behavior of stochastic models relating to a wide range of quantitative properties, such as runtime, energy consump…
Logic-based Reward Shaping for Multi-Agent Reinforcement Learning
Ingy ElSayed-Aly, Lu Feng
Reinforcement learning (RL) relies heavily on exploration to learn from its environment and maximize observed rewards. Therefore, it is essential to design a reward function that g…
Safe Multi-Agent Reinforcement Learning via Shielding
Ingy Elsayed-Aly, Suda Bharadwaj, Christopher Amato +3
Multi-agent reinforcement learning (MARL) has been increasingly used in a wide range of safety-critical applications, which require guaranteed safety (e.g., no unsafe states are ev…